homelab

Media production by an agent on a machine with an 8 GB GPU and commercial licensing, one skill per modality with rules that hold for any model: image and video generation, image retouching, transparent looping cut-outs for web pages, a mechanical check of a web page, voice-over at -16 LUFS, music and sound, stock media with per-item licenses, video composed as code, editing finished video, a 3D product turntable, scripted 3D scenes with characters in Blender, and sourcing rules for factual videos. Two hooks warn: where vipsthumbnail -o really writes, and when Kinocut runs before any skill is loaded.

13 skills · 1 MCP server · hooks

What fails silently when an agent works on a mobile app: device layer (adb, emulator, UI dumps, mirroring a phone) and bundler layer (Expo, Metro, prebuild). Narrow PreToolUse guards that warn and never block, and the Maestro MCP server for driving UI flows on a device.

5 skills · 1 MCP server · hooks

Rules for multi-agent work: model routing per phase, fan-out sizing, closed output schemas and citation checks, with CLI workers for search and extract and hooks that load the rules and check routing at dispatch.

1 skill · hooks

Another vendor's agent CLI as an isolated subagent, from any host: ask a read-only question or hold a multi-turn conversation (agy, opencode, Codex, Grok, Hermes, Copilot, Cursor, Muse, Kimi, or Claude Code from another host), get a second opinion on a diff, or delegate one coding slice to agy, opencode, Copilot, Codex, Grok, Cursor or Claude Code under the worker CLI's own hooks and a mechanical gate. Tiers (cheap, mid, top) map to a model and effort per backend. The verdict never reads the CLI's exit 0 as success.

1 skill · hooks

Pins the installed game's version before the agent answers from training memory: a UserPromptSubmit hook reads Steam appmanifests and injects appid, buildid, update date and the patch-notes URL, and a skill routes the question and weighs sources against the last patch.

1 skill · hooks

Writes, trims and audits a repository's AGENTS.md: what belongs in it, what to cut, size limits per tool, and a stdlib checker for missing commands, dead paths, oversize files and a CLAUDE.md that hides AGENTS.md.

1 skill

Transform Claude into an Azure expert. This plugin integrates the Azure MCP server and specialized Azure skills to move beyond generic advice. It enables Claude to perform real-world tasks: listing resources, validating deployments, diagnosing infrastructure issues, and optimizing costs across 50+ Azure services.

44 skills · 1 MCP server

CI/CD pipeline configuration, GitHub Actions/GitLab CI workflow setup, and automated deployment pipeline orchestration

4 skills · 1 command · 5 agents

Build, manage, and deploy Wix sites and apps. Includes CLI development skills and Wix MCP server for site management, eCommerce, CMS, dashboard extensions, and more.

37 skills · 1 MCP server

Build, launch, grade, and schedule Claude Managed Agents (CMA) in your own Anthropic account — a plugin re-implementation of Anthropic's launch-your-agent reference skill (Apache-2.0; independent, not a fork). Every session starts with a goal (./my-agent/goal.json, opt-in SessionStart hook, driven by /cs-goal); loop_compiler.py compiles it into a bounded grade->iterate loop (max_iterations 1..20), a recurring cron scheduled-deployment loop, or a single-pass interview->stage->launch workflow. 6 skills: orchestrator (context: fork goal router) + interview + stage-launch + grade-iterate + run-without-you + wrap-up. 18 stdlib-only deterministic scaffolders (no network/API calls; live launches emitted as BYOK curl that never prints the key), 4 agents, 8 commands, hooks, 5 references, 4 assets. Validators enforce CMA limits. Distinct from engineering/agent-harness (generic domain loop) and write-a-skill (authors Claude Code skills, not CMAs).

6 skills · 8 commands · 4 agents · hooks

DevOps, cloud, and deployment specialists - Kubernetes, Terraform, AWS, Azure, GCP, and SRE

Production LLM inference including vLLM, TensorRT-LLM, llama.cpp, and SGLang. Use when deploying models for production inference.

98 skills